Job description

About the Role We’re looking for a Generative AI Data Scientist to design, train, and optimize AI models that power next-generation intelligent systems. You’ll work on projects involving large language models (LLMs), NLP, and multimodal data pipelines — helping turn research into production-grade products. Responsibilities • Develop and fine-tune generative AI models (LLMs, diffusion, transformer-based architectures). • Build and manage data pipelines for model training, evaluation, and continuous learning. • Design prompt engineering and retrieval-augmented generation (RAG) frameworks. • Collaborate with engineers and product teams to deploy scalable inference APIs. • Evaluate model performance, bias, and data quality; implement monitoring systems. • Contribute to model interpretability, safety, and responsible AI practices. Qualifications • MS or PhD in Computer Science, Machine Learning, Statistics, or related field. • 3+ years of experience in ML/AI, with exposure to generative or transformer-based models. • Strong Python skills (PyTorch, TensorFlow, Hugging Face, LangChain, etc.). • Experience with vector databases, RAG, and fine-tuning open-weight models (e.g., Llama, Mistral). • Familiarity with cloud ML environments (AWS Sagemaker, GCP Vertex, or Azure ML). • Excellent problem-solving and communication skills. Nice to Have • Experience deploying AI systems in production. • Knowledge of multimodal (text, image, audio) model training. • Contributions to open-source AI projects or published research. What We Offer • Competitive compensation • Flexible work environment. • Opportunity to work on frontier AI systems with real-world impact.

Requirements